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Conference Papers

  1. P. Ghamisi, F. Sepehrband, A. Mohammadzadeh, M. Mortazavi, and J. Choupan, "Fast and Efficient Algorithm for Real-Time Lossless Compression of LiDAR rasterized data Based on Improving Energy Compaction," The 6th IEEE GRSS and ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas, JURSE'11, Munich, Germany, April 2011.

  2. F. Sepehrband, P. Ghamisi, M. Mortazavi, and J. Choupan, "Simple and efficient remote sensing image transformation for lossless compression," Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 82854A (September 30, 2011); doi:10.1117/12.913262.

  3. F. Sepehrband, P. Ghamisi, M. Mortazavi, and J. Choupan, "Simple and Efficient Remote Sensing Image Transformation for Lossless Compression," International Conference on Signal and Information Processing (ICSIP'10), Changsha, China, December, 2010.

  4. P. Ghamisi, F. Sepehrband, J. Choupan, and M. Mortazavi, "Binary Hybrid GAPSO based algorithm for compression of hyperspectral data," Signal Processing and Communication Systems (ICSPCS), vol., no., pp.1-8, 12-14 Dec. 2011; doi: 10.1109/ICSPCS.2011.6140839.

  5. P. Ghamisi and L. Kumar, "A novel adaptive compression method for hyperspectral images by using EDT and particle swarm optimization," Proc. SPIE 8299, Digital Photography VIII, 82990M (January 24, 2012); doi:10.1117/12.904727.

  6. P. Ghamisi, M. S. Couceiro, N. M. F. Ferreira, and L. Kumar, "Use of Darwinian Particle Swarm Optimization technique for the segmentation of Remote Sensing images," IGARSS 2012, vol., no., pp.4295-4298, 22-27 July 2012, doi: 10.1109/IGARSS.2012.6351718.

  7. P. Ghamisi, M. S. Couceiro, and J. A. Benediktsson, "Extending the Fractional Order Darwinian Particle Swarm Optimization to Segmentation of Hyperspectral Images," in Proc. SPIE, Image and Signal Processing for Remote Sensing XVIII, 2012, pp. 85370F-85370F-11.

  8. P. Ghamisi, M. S. Couceiro, M. Fauvel, and J. A. Benediktsson, "Spectral-Spatial Classification Based on Integrated Segmentation," in Proc. IEEE IGARSS, 2012, pp. 1458-1461, 2013.

  9. P. Ghamisi, Jon Atli Benediktsson, and Magnus O. Ulfarsson, "The Spectral Spatial Classification of Hyperspectral Images Based on Hidden Markov Random Field and its Expectation-Maximization," in Proc. IEEE IGARSS, 2013, pp. 1107-1110, [The winner of the IEEE Mikio Takagi student prize 2013 for winning the Student Paper Competition at the conference between almost 70 people].

  10. P. Ghamisi, M. S. Couceiro, and J. A. Benediktsson, "Classication of Hyperspectral Images with Binary Fractional Order Darwinian PSO and Random Forests," in Proc. SPIE, Image and Signal Processing for Remote Sensing XIX, 2013, pp. 88920S88920S-8.

  11. P. Ghamisi, M. S. Couceiro, and J. A. Benediktsson, "FODSPO Based Feature Selection for Hyperspectral Remote Sensing Data," WHISPERS 2014, Lausane, Switzerland.

  12. P. Ghamisi, J. A. Benediktsson, and S. Phinn, "Fusion of Hyperspectral and LiDAR Data in Classification of Urban Areas," in Proc. IEEE IGARSS, 2014, pp. 181-184, [Invited paper].

  13. P. Ghamisi and J. A. Benediktsson, "Feature Selection of Hyperspectral Data by Considering the Integration of Genetic Algorithms and Particle Swarm Optimization," in Proc. SPIE, Image and Signal Processing for Remote Sensing XX, 2014, pp. 92440J-92440J-6.

  14. P. Ghamisi, D. Wu, G. Cavallaro, J. A. Benediktsson, S. Phinn, and N. Falco, "An advanced classier for the joint use of LiDAR and hyperspectral data: Case study in Queensland, Australia," 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, 2015, pp. 2354-2357.

  15. Y. Chen, C. Li, P. Ghamisi, and C. Shi, "Convolutional neural network fusion of hyperspectral and LiDAR data for thematic classication," 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China.

  16. P. Ghamisi, R. Souza, L. Rittner, J. A. Benediktsson, R. Lotufo, and X. X. Zhu, "Extinction profiles: A novel approach for the analysis of remote sensing," 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China.

  17. P. Ghamisi, R. Souza, J. A. Benediktsson, X. X. Zhu, L. Rittner, and R. Lotufo, "Extended extinction profile for the classification of hyperspectral images," WHISPERS 2016, Los Angles, California.

  18. N. Yokoya and P. Ghamisi, "Land-Cover monitoring using time-series hyperspectral data via fractional-order Darwinian particle swarm optimization Segmentation," WHISPERS 2016, Los Angles, California.

  19. J. Hu, P. Ghamisi, A. Schmitt, and X. X. Zhu, "Object based fusion of polarimetric SAR and hyperspectral imaging for land use classification," WHISPERS 2016, Los Angles, USA.

  20. N. He, L. Fang, S. Li, P. Ghamisi, and J. A. Benediktsson, "Hyperspectral Images Classification by Fusing Extinction Profiles Feature," IGARSS 2017, 2017.

  21. P. Ghamisi, B. Rasti, and X. X. Zhu, "Feature Fusion of Hyperspectral and LiDAR Data Using Extinction Profiles and Total Variation," IGARSS 2017, 2017.

  22. J. Hu, Y. Wang, P. Ghamisi, and X. X. Zhu, "Evaluation of PolSAR Similarity Measures with Spectral Clustering," IGARSS 2017, 2017.

  23. L. Mou, P. Ghamisi, and X. X. Zhu, "Fully Conv-Deconv Network for Unsupervised Spectral-Spatial Feature Extraction of Hyperspectral Imagery via Residual Learning," IGARSS 2017, accepted, [Invited paper].

  24. P. Du, J. Xia, P. Ghamisi, A. Iwasaki, and J. A. Benediktsson, "Multiple Composite Kernel Learning for Hyperspectral Image Classification." IGARSS 2017, 2017.

  25. N. Yokoya and P. Ghamisi, "Multimodal, Multitemporal, and Multisource Global Data Fusion for Local Climate Zones Classification Based on Ensemble Learning," IGARSS 2017, 2017.

  26. C. P. Qiu, M. Schmitt, P. Ghamisi, and X. X. Zhu, "Effect of the Training Set Configuration on Sentinel-2-Based Urban Local Climate Zone Classification," Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 931-936, https://doi.org/10.5194/isprs-archives-XLII-2-931-2018, 2018. 

  27. R. Gloaguen et al., "Multi-Source and multi-Scale Imaging-Data Integration to boost Mineral Mapping," IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 5587-5589.

  28. X. Wu, D. Hong, P. Ghamisi, W. Li, and R. Tao, "LW-ODF: A Light-Weight Object Detection Framework for Optical Remote Sensing Imagery," IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 1462-1465.

  29. B. Rasti, P. Ghamisi, and R. Gloaguen, "Multisensor Feature Fusion Using Low-Rank Modeling and Component Analysis," IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 4811-4814.

  30. P. Ghamisi, B. Rasti, and R. Gloaguen, "A Novel Composite Kernel Approach for Multisensor Remote Sensing Data Fusion," IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 2507-2510.

  31. C. Contreras, M. Khodadadzadeh, P. Ghamisi, and R. Gloaguen, "Mineral Mapping of Drill Core Hyperspectral Data with Extreme Learning Machines," IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 2686-2689.

  32. K. R. Shahi, et al. "A New Spectral-spatial Subspace Clustering Algorithm for Hyperspectral Image Analysis," ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol.-3-2020, 2020, pp. 185-191. 

  33. P. Duan, P. Ghamisi, R. Jackisch, X. Kang, R. Gloaguen, and S. Li, "Intrinsic Image Decomposition-Based Resolution Enhancement for Mineral Mapping," IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, 2020, pp. 4112-4115.

  34. B. Rasti, P. Ghamisi, and R. Gloaguen, "Fusion of Multispectral LiDAR and Hyperspectral Imagery," IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, 2020, pp. 2659-2662.

  35. R. Gloaguen, M. Kirsch, S. Lorenz, R. Booysen, R. Zimmermann, P. Ghamisi, and B. Rasti, "Towards 4D Virtual Outcrops with Hyperspectral Imaging," IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, 2020, pp. 4035-4036.

  36. P. Duan, J. Kang, X. Kang, P. Ghamisi, and S. Li, "Sun Glint Removal of Hyperspectral Images via Texture-Aware Total Variation," IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, 2020, pp. 7005-7008.

  37. P. Ghamisi, H. Li, R. Jackisch, B. Rasti, and R. Gloaguen, "Remote Sensing and Deep Learning for Sustainable Mining," IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, 2020, pp. 3739- 3742.

  38. K. R. Shahi, P. Ghamisi, R. Jackisch, B. Rasti, P. Scheunders, and R. Gloaguen, "A Multi-Sensor Subspace-Based Clustering Algorithm Using RGB and Hyperspectral Data," 2021 11th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2021, pp. 1-5.

  39. B. Rasti, B. Koirala, P. Scheunders, and P. Ghamisi, "Spectral Unmixing Using Deep Convolutional Encoder-Decoder," 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021, pp. 3829-3832.

  40. B. Rasti, B. Koirala, P. Scheunders, P. Ghamisi, and R. Gloaguen, "Boosting Hyperspectral Image Unmixing Using Denoising: Four Scenarios," 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021, pp. 3821-3824.

  41. K. R. Shahi, B. Rasti, P. Ghamisi, P. Scheunders, and R. Gloaguen, "When is the Right Time to Apply Denoising?," 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021, pp. 2464-2467.

  42. K. R. Shahi, P. Ghamisi, R. Jackisch, B. Rasti, P. Scheunders, and R. Gloaguen, "A Multi-Sensor Subspace-Based Clustering Algorithm Using RGB and Hyperspectral Data," 2021 11th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2021, pp. 1-5.

  43. A. Gruca, P. Herruzo, P. Rpodas, A. Kucik, C. Briese, M. K. Kopp, S. Hochreiter, P. Ghamisi, and D. P. Kreil, "CDCEO’21 - First Workshop on Complex Data Challenges in Earth Observation," In Proceedings of the 30th ACM International Conference on Information & Knowledge Management (CIKM), 2021. Association for Computing Machinery, New York, NY, USA, 48784879.

  44. S. Chang and P. Ghamisi, "Hyperspectral Anomaly Detection based on Low-rank Structure Exploration," In CIKM Workshops 2021.

  45. Y. Xu and P. Ghamisi, "Region-Growing Fully Convolutional Networks for Hyperspectral Image Classification with Point-Level Supervision," In CIKM Workshops 2021.

  46. LE La Rosa, DA. Oliveira, S. Thiele, P. Ghamisi, and R. Gloaguen, "Weak-Supervision Based on Label Proportions for Earth Observation Applications from Optical and Hyperspectral Imagery," In IJCAI Workshops 2022.

  47. S. Chang, M. Kopp, and P. Ghamisi, "A Deep Feature Retrieved Network for Bitemporal Remote Sensing Image Change Detection," In IJCAI Workshops 2022.

  48. Y. Xu, W. Yu, and P. Ghamisi, "Task-Guided Denoising Network for Adversarial Defense of Remote Sensing Scene Classification," In IJCAI Workshops 2022.

  49. H. Shahabi et al., "Rapid Mapping of Landslides from Sentinel-2 Data Using Unsupervised Deep Learning," 2022 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS), 2022, pp. 17-20.

  50. M. Schmitt, P. Ghamisi, N. Yokoya, and R. Hänsch, "EOD: The IEEE GRSS Earth Observation Database," IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, 2022, pp. 5365-5368.

  51. K. R. Shahi, P. Ghamisi, B. Rasti, P. Scheunders, and R. Gloaguen, "Hyperspectral Clustering Using Atrous Spatial-Spectral Convolutional Network," IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, 2022, pp. 199-202.

  52. B. Rasti, P. Ghamisi, and R. Gloaguen, "Unsupervised Deep Hyperspectral Inpainting Using a New Mixing Model," IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, 2022, pp. 1221-1224.

  53. D. Coquelin, B. Rasti, M. Götz, P. Ghamisi, R. Gloaguen, and A. Streit, "Hyde: The First Open-Source, Python-Based, Gpu-Accelerated Hyperspectral Denoising Package," 2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2022, pp. 1-5 [code].

  54. S. Chouhan, B. Rasti, P. Ghamisi, S. Lorenz, M. Fuchs, and R. Gloaguen, "Hyperspectral Unmixing Using Convolutional Autoencoder For Metal Detection In Lithium-Ion Battery Recycling Applications," 2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2022, pp. 1-5.

  55. Thiele, S., Afifi, A.J., Lorenz, S., Tolosana-Delgado, R., Kirsch, M., Ghamisi, P. and Gloaguen, R., 2023, May. LithoNet: A benchmark dataset for machine learning with digital outcrops. In EGU General Assembly Conference Abstracts (pp. EGU-14007).

  56. Rasti, B., Jain, A., Fuchs, M., Ghamisi, P. and Gloaguen, R., 2023, July. Hyperspectral Domain Adaptation for the Detection of Material Types in Recycling Streams at the Example of Electrolyzers. In IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium (pp. 7618-7620). IEEE.

  57. Hernandez-Sequeira, I., Fernandez-Beltran, R., Xu, Y., Ghamisi, P. and Pla, F., 2023, September. Semi-supervised Classification for Remote Sensing Datasets. In International Conference on Image Analysis and Processing (pp. 463-474). Cham: Springer Nature Switzerland.

  58. Arbash, E., de Lima Ribeiro, A., Thiele, S., Gnann, N., Rasti, B., Fuchs, M., Ghamisi, P. and Gloaguen, R., 2023, October. Masking hyperspectral imaging data with pretrained models. In 2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) (pp. 1-5). IEEE.

  59. Koirala, B., Das, S., Rasti, B., Ghamisi, P., Gloaguen, R. and Scheunders, P., 2023, October. Acritical Comparison of Linear and Nonlinear Unmixing for Intimate Mixtures. In 2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) (pp. 1-5). IEEE.

  60. Das, S., Ghamisi, P. and Gloaguen, R., 2023, October. Open Geology Database (OGD): An Integrated Platform for Geological, Mining, and Seismic Datasets for Open Research. In 2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) (pp. 1-5). IEEE [code].

  61. Faruk, M.O., Rasti, B., Fuchs, M., Gloaguen, R. and Ghamisi, P., 2023, October. Deep Learning-Based Architectures For Multimodal Instance Segmentation. In 2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) (pp. 1-5). IEEE.

  62. Rizaldy, A., Afifi, A.J., Ghamisi, P. and Gloaguen, R., 2023, October. Transformer-Based Models for Hyperspectral Point Clouds Segmentation. In 2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) (pp. 1-5). IEEE.

  63. Shahabi, H., Ghorbanzadeh, O., Homayouni, S. and Ghamisi, P., 2024. A Comparison of SimCLR and SwAV Contrastive Self-Supervised Learning Models For Landslide Detection (No. EGU24-4772). Copernicus Meetings.

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